/fitting-with-mlp-using-pytorch

Fitting problems solved with a multilayer perceptron implemented in PyTorch technology

Primary LanguagePythonMIT LicenseMIT

Fitting with MLP using PyTorch

Goal of this repository is to share programs that fit some kinds of curves by high configurable multilayer perceptron (MLP) neural network written in Python 3 using PyTorch.

One-variable real-valued function fitting

The project One-variable real-valued function fitting implements the fitting of a continuous and limited real-valued function defined in a closed interval of the reals.
Please visit here for concepts about this project.

Parametric curve on plane fitting

The project Parametric curve on plane fitting implements the fitting of a continuous and limited real-valued parametric curve on plane where parameter belongs to a closed interval of the reals. It implements two alternative techniques: the official one implements one MLP that fits a vector function f(t) = [x(t), y(t)] instead the 'twin' variant implements a pair of twins of MLPs that fit separately the one variable functions x(t) and y(t).
Please visit here for concepts about this project.

Parametric curve in space fitting

The project Parametric curve in space fitting implements the fitting of a continuous and limited real-valued parametric curve in space where parameter belongs to a closed interval of the reals. It implements one MLP that fits a vector function f(t) = [x(t), y(t), z(t)].
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Two-variables real-valued function fitting

The project Two-variables real-valued function fitting implements the fitting of a continuous and limited two variables real-valued function constrained in a rectangle.
Please visit here for concepts about this project.